ehristoforu commited on
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Update app (13).py

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  1. app (13).py +5 -5
app (13).py CHANGED
@@ -7,19 +7,19 @@ from model import run
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  HF_PUBLIC = os.environ.get("HF_PUBLIC", False)
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- DEFAULT_SYSTEM_PROMPT = "You are CodeLlama. You are AI-assistant, you are polite, give only truthful information and are based on the CodeLLaMA-34B model from Meta. You can communicate in different languages equally well."
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  MAX_MAX_NEW_TOKENS = 4096
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  DEFAULT_MAX_NEW_TOKENS = 1024
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  MAX_INPUT_TOKEN_LENGTH = 4000
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  DESCRIPTION = """
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- # CodeLlama-34B Chat
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- πŸ’» This Space demonstrates model [CodeLlama-34b-Instruct](https://huggingface.co/codellama/CodeLlama-34b-Instruct-hf) by Meta, a Code Llama model with 34B parameters fine-tuned for chat instructions and specialized on code tasks. Feel free to play with it, or duplicate to run generations without a queue! If you want to run your own service, you can also [deploy the model on Inference Endpoints](https://huggingface.co/inference-endpoints).
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- πŸ”Ž For more details about the Code Llama family of models and how to use them with `transformers`, take a look [at our blog post](https://huggingface.co/blog/codellama) or [the paper](https://huggingface.co/papers/2308.12950).
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- πŸƒπŸ» Check out our [Playground](https://huggingface.co/spaces/codellama/codellama-playground) for a super-fast code completion demo that leverages a streaming [inference endpoint](https://huggingface.co/inference-endpoints).
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  """
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  HF_PUBLIC = os.environ.get("HF_PUBLIC", False)
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+ DEFAULT_SYSTEM_PROMPT = "You are Mistral. You are AI-assistant, you are polite, give only truthful information and are based on the Mistral-7B model from Mistral AI. You can communicate in different languages equally well."
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  MAX_MAX_NEW_TOKENS = 4096
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  DEFAULT_MAX_NEW_TOKENS = 1024
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  MAX_INPUT_TOKEN_LENGTH = 4000
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  DESCRIPTION = """
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+ # Mistral-7B Chat
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+ πŸ’» This Space demonstrates model [Mistral-7b-Instruct](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) by Mistral AI, a Mistral-chat model with 7B parameters fine-tuned for chat instructions and specialized on many tasks. Feel free to play with it, or duplicate to run generations without a queue! If you want to run your own service, you can also [deploy the model on Inference Endpoints](https://huggingface.co/inference-endpoints).
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+ πŸ”Ž For more details about the Mistral family of models and how to use them with `transformers`, take a look [at our blog post](https://huggingface.co/blog/mistral).
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+ πŸƒπŸ» Check out our [Playground](https://huggingface.co/spaces/osanseviero/mistral-super-fast) for a super-fast code completion demo that leverages a streaming [inference endpoint](https://huggingface.co/inference-endpoints).
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  """
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